The present invention relates to neuromorphic and synapatronic systems, and in particular, producing spike-timing dependent plasticity in a synapse cross-bar array.
Neuromorphic and synapatronic systems, also referred to as artificial neural networks, are computational systems that permit electronic systems to essentially function in a manner analogous to that of biological brains. Neuromorphic and synapatronic systems do not generally utilize the traditional digital model of manipulating 0s and 1s. Instead, neuromorphic and synapatronic systems create connections between processing elements that are roughly functionally equivalent to neurons of a biological brain. Neuromorphic and synapatronic systems may be comprised of various electronic circuits that are modeled on biological neurons.
In biological systems, the point of contact between an axon of a neuron and a dendrite on another neuron is called a synapse, and with respect to the synapse, the two neurons are respectively called pre-synaptic and post-synaptic. The essence of our individual experiences is stored in conductance of the synapses. The synaptic conductance changes with time as a function of the relative spike times of pre-synaptic and post-synaptic neurons, as per spike-timing dependent plasticity (STDP). The STDP rule increases the conductance of a synapse if its post-synaptic neuron fires after its pre-synaptic neuron fires, and decreases the conductance of a synapse if the order of the two firings is reversed.